How to Use the Cleared (ClearedIn) MCP in Google ADK

Q: How can I use Google ADK to get Cleared (ClearedIn) audit logs into BigQuery?

Your Gemini agent calls the listclearedauditlogs tool to get the data. From there, you just need a simple Python function in your agent's code to write the structured output to the right BigQuery table.

Q: Does the Cleared (ClearedIn) MCP Server work with Gemini's long context via Google ADK?

Yes. The server provides the raw data from tools like listbackgroundscreenings. You can feed large volumes of that data into a Gemini model, which can then reason over the entire set to answer complex questions.

Q: Can I limit my Google ADK agent to only read-only actions for Cleared (ClearedIn)?

Definitely. When you initialize the McpToolset, use the toolnames parameter to provide a list of allowed tools. For a read-only agent, you would only include the list and get tools.

Q: What's the setup for Google ADK and this MCP server?

It's a pip install google-adk and then one line to define the McpToolset, pointing it to your Vinkius server URL. You then pass that toolset to your agent.

Connect Gemini agents to your Cleared (ClearedIn) account with this MCP Server and Google ADK to act on identity data inside Google Cloud.

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Connect Cleared (ClearedIn) MCP to Google ADK

Create your Vinkius account to connect Cleared (ClearedIn) to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Cleared (ClearedIn) with Google ADK

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Analyze Audit Logs at Scale

This MCP server plugs right into your Google Cloud environment. Have your agent call `list_cleared_audit_logs`, and you can pipe thousands of security events directly into a BigQuery table for analysis. No more manual exports. Here's where it gets interesting. With Gemini's long-context window, you can feed that massive dataset to your agent and ask it to find anomalies or summarize patterns across months of data. It's a powerful way to turn raw logs into actual security insights.

Build Enterprise Workflows on GCP

Trigger Cleared actions from events anywhere in your Google Cloud infrastructure. A new file in a bucket or an alert from Security Command Center can kick off a Gemini agent to check on a user's status. For example, the agent can run `list_identity_verifications` for a user and then use `get_verification_details` to confirm their status. It connects your existing GCP signals to real-world identity checks without you writing a bunch of glue code.

Control Agent Access to this MCP Server

Google ADK gives you tight control over what your agents can do. When you set up the `McpToolset`, you can pass a `tool_names` filter to expose only the tools you want a specific agent to have. If you're building a read-only agent for analysts, you can restrict it to just the `list_*` and `get_*` functions. This prevents an agent from accidentally trying to perform an action it shouldn't, which is critical for enterprise use cases.

Setup guide

Set up Cleared (ClearedIn) MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Cleared (ClearedIn) tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Cleared (ClearedIn)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Cleared (ClearedIn) tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Cleared (ClearedIn). All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Cleared (ClearedIn) MCP in Google ADK

Your Gemini agent calls the `list_cleared_audit_logs` tool to get the data. From there, you just need a simple Python function in your agent's code to write the structured output to the right BigQuery table.

Yes. The server provides the raw data from tools like `list_background_screenings`. You can feed large volumes of that data into a Gemini model, which can then reason over the entire set to answer complex questions.

Definitely. When you initialize the `McpToolset`, use the `tool_names` parameter to provide a list of allowed tools. For a read-only agent, you would only include the `list_*` and `get_*` tools.

It's a `pip install google-adk` and then one line to define the `McpToolset`, pointing it to your Vinkius server URL. You then pass that toolset to your agent.

The server handles sensitive background screening results and digital signature details. Each request you send is processed in a dedicated, zero-trust container on Vinkius that is created on-demand and destroyed immediately after.

Use it with your favorite AI tools

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